Linear Algebra for Data Science
Approximation error is the difference between the actual value of a quantity and the value that is estimated or approximated. This concept is particularly relevant when dealing with large-scale data, where exact calculations may be impractical or impossible, making approximations essential for efficiency. Understanding approximation error is crucial for evaluating the effectiveness of various sketching techniques used to represent large datasets while minimizing data loss.
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